量化回测框架-backtrader-KD策略_backtrader kd策略-优快云博客

本文链接：https://blog.youkuaiyun.com/guosuming/article/details/108302181

本文介绍如何利用backtrader量化交易框架，结合KD（相对强弱指数）策略进行股票或期货的回测分析。首先，详细解释KD指标的计算原理及其在交易中的应用。接着，演示如何在backtrader中实现KD指标的计算，并将其融入交易策略。通过实例展示如何设置买入和卖出信号，完成策略的编写，并进行回测，分析策略的收益、风险等关键指标。

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from datetime import datetime
import backtrader
import pandas

def Function_For_Build_KD_Object(KD_Period):
    
    
    class Strategy_KD_Object(backtrader.Strategy):
        
        def __init__(self):
    
            self.data_open = self.datas[0].open
            self.data_high = self.datas[0].high
            self.data_low = self.datas[0].low
            self.data_close = self.datas[0].close
            self.data_volume = self.datas[0].volume  
            
            self.RSV_Value = 0
            self.K_Value = 50
            self.D_Value = 50            
            
        def next(self):
            
            def Function_Cauculate_KD (KD_Period) :
                
                Highest_Price =  self.data_high[0]
                Lowest_Price =  self.data_low[0]
                
                for Day in range(0, -KD_Period, -1):
                    
                    if self.data_high[Day] > Highest_Price :
                        Highest_Price = self.data_high[Day]

                    if self.data_low[Day] < Lowest_Price :
                        Lowest_Price = self.data_low[Day]
                        
                RSV_Value = 100 * (self.data_close[0] - Lowest_Price) / (Highest_Price - Lowest_Price)
                
                self.K_Value = (self.K_Value * (2/3)) + (RSV_Value * (1/3))
                self.D_Value = (self.D_Value * (2/3)) + (self.K_Value * (1/3))
                
           
            Function_Cauculate_KD(KD_Period)
            
            #self.buy()
            #self.sell()
            #https://www.backtrader.com/docu/order-creation-execution/order-creation-execution/

            if self.K_Value > self.D_Value:
                self.buy()
                print("buy")
                
            if self.K_Value < self.D_Value:
                self.sell()
                print("sell")
            
            
            data_fram = pandas.DataFrame({"Open Price": self.data_open[0],
                                             "High Price": self.data_high[0],
                                             "Low Price": self.data_low[0],
                                             "Close Price": self.data_close[0],
                                             "Volumns": self.data_volume[0],
                                             "K Value": self.K_Value,
                                             "D Value": self.D_Value
                                             },index=[0])
            print(data_fram)
            
            
    return Strategy_KD_Object